Abstract

Model Predictive Control (MPC) is a well established control strategy that is being used in an increasingly wider set of application areas. Unfortunately, the requirement of an on-line solution to a constrained optimization problem is an impediment for its application to fast dynamics plants. The hardware implementation of target-optimized, application-specific controllers on reconfigurable Field Programmable Gate Arrays (FPGA) can widespread the use of MPC to control systems that demand short sampling periods. This paper describes a first approach to the design and implementation of a fixed-point arithmetic model predictive controller adapted to a benchmark control problem with constraints. A FPGA chip is a suitable hardware platform to implement the tailored controller as it allows for its adaptation to other operating requirements and to different target systems while meeting real time constraints.

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